COVID-19 Future Forecasting based on Time-series statistical analysis using Machine Learning Model

ABSTRACT

The epidemic COVID-19 has shaken the globe through its cruelty, and its spread rate continues to rise daily. This paper highlights the clinical stance in the COVID-19 research studies, where time-series statistical analysis has been performed by using Prophet Model. It is widely used to understand the trend of the current epidemic after 2nd May 2020 with data at the worldwide state. The prophet model is an open-source model obtained by the data science panel on Facebook for performing predicting operations. It assists to make fast and accurate predictions for existing data samples. The Prophet model is simple to implement because its open authorized repository exists on GitHub. The time-series data analysis refers to the confirmed, recovered, and death rates for the time of 2nd May 2021 to 17th January 2022. The statistical validation strategy is followed by the implementation of a T-test on the evaluated time-series data. The expected data generated by the predictive model can be further used by the official authorities, medical departments of various countries. Moreover, the model is used to provide new graphical insights into past, present, and future trends. © 2021 Copyright for this paper by its authors.